3 citations · 7 across the 3 of their papers we have counts for
3 papers
eess.SY2024★ 2 cited
Security and Privacy of Digital Twins for Advanced Manufacturing: A Survey
Alexander D. Zemskov, Yao Fu, Runchao Li +9
In Industry 4.0, the digital twin is one of the emerging technologies, offering simulation abilities to predict, refine, and interpret conditions and operations, where it is crucia…
cs.LG2024★ 2 cited
A Digital Twin Framework Utilizing Machine Learning for Robust Predictive Maintenance: Enhancing Tire Health Monitoring
Vispi Karkaria, Jie Chen, Christopher Luey +4
We introduce a novel digital twin framework for predictive maintenance of long-term physical systems. Using monitoring tire health as an application, we show how the digital twin f…
cs.LG2024★ 3 cited
Towards a Digital Twin Framework in Additive Manufacturing: Machine Learning and Bayesian Optimization for Time Series Process Optimization
Vispi Karkaria, Anthony Goeckner, Rujing Zha +6
Laser-directed-energy deposition (DED) offers advantages in additive manufacturing (AM) for creating intricate geometries and material grading. Yet, challenges like material incons…